// GET: MultiFaceDetection
public async Task <ActionResult> Index()
{
try
{
// Step 1. Get images from AWS S3 storage.
List <string> imagesNames = new List <string>
{
"Deepika_5.jpg",
"deepika-padukone-story_647_112417055722.jpg",
"Disha_Patani_promotes_M.S._Dhoni_–_The_Untold_Story_(05).jpg",
"Disha-Patani-1.jpg",
"elizabeth-olsen-explains-why-singing-badly-on-purpose-for-her-new-movie-was-freeing.jpg",
"female-superheroes-black-widow.jpg",
"olsens.jpg",
"Scarlett_Johansson_in_Kuwait_01b-tweaked.jpg",
"alexandra_daddario_2015-wide.jpg",
"Jacqueline-Fernandez.jpg"
};
// Step 2. For each image, run the face api detection algorithm.
var faceServiceClient = new FaceServiceClient(ServiceKey, "https://westcentralus.api.cognitive.microsoft.com/face/v1.0");
for (int i = 0; i < imagesNames.Count; i++)
{
var detectedFaces = new ObservableCollection <vmFace>();
var resultCollection = new ObservableCollection <vmFace>();
using (WebClient client = new WebClient())
{
byte[] fileBytes = client.DownloadData(string.Concat("https://s3-eu-west-1.amazonaws.com/faceapiimages/", imagesNames[i]));
bool exists = System.IO.Directory.Exists(Server.MapPath(directory));
if (!exists)
{
try
{
Directory.CreateDirectory(Server.MapPath(directory));
}
catch (Exception ex)
{
ex.ToString();
}
}
string imageRelativePath = "../MultiDetectedFiles" + '/' + imagesNames[i];
string imageFullPath = Server.MapPath(directory) + '/' + imagesNames[i] as string;
System.IO.File.WriteAllBytes(imageFullPath, fileBytes);
using (var stream = client.OpenRead(string.Concat("https://s3-eu-west-1.amazonaws.com/faceapiimages/", imagesNames[i])))
{
Face[] faces = await faceServiceClient.DetectAsync(stream, true, true, new FaceAttributeType[] { FaceAttributeType.Gender, FaceAttributeType.Age, FaceAttributeType.Smile, FaceAttributeType.Glasses });
Bitmap CroppedFace = null;
foreach (var face in faces)
{
//Create & Save Cropped Images
var croppedImg = Convert.ToString(Guid.NewGuid()) + ".jpeg" as string;
var croppedImgPath = "../MultiDetectedFiles" + '/' + croppedImg as string;
var croppedImgFullPath = Server.MapPath(directory) + '/' + croppedImg as string;
CroppedFace = CropBitmap(
(Bitmap)Bitmap.FromFile(imageFullPath),
face.FaceRectangle.Left,
face.FaceRectangle.Top,
face.FaceRectangle.Width,
face.FaceRectangle.Height);
CroppedFace.Save(croppedImgFullPath, ImageFormat.Jpeg);
if (CroppedFace != null)
{
((IDisposable)CroppedFace).Dispose();
}
detectedFaces.Add(new vmFace()
{
ImagePath = imageRelativePath,
FileName = imagesNames[i],
FilePath = croppedImgPath,
Left = face.FaceRectangle.Left,
Top = face.FaceRectangle.Top,
Width = face.FaceRectangle.Width,
Height = face.FaceRectangle.Height,
FaceId = face.FaceId.ToString(),
Gender = face.FaceAttributes.Gender,
Age = string.Format("{0:#} years old", face.FaceAttributes.Age),
IsSmiling = face.FaceAttributes.Smile > 0.0 ? "Smile" : "Not Smile",
Glasses = face.FaceAttributes.Glasses.ToString(),
});
}
// Convert detection result into UI binding object for rendering.
var imageInfo = UIHelper.GetImageInfoForRenderingFromStream(stream);
var rectFaces = UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo);
foreach (var face in rectFaces)
{
resultCollection.Add(face);
}
var faceModal = new FaceDetectionModal {
DetectedFaces = detectedFaces, ResultCollection = resultCollection
};
this.finalModal.Items.Add(faceModal);
}
}
}
}
catch (Exception ex)
{
Console.Write(ex);
throw;
}
return(View(this.finalModal));
}
// GET: MultiFaceDetection
public async Task <ActionResult> Index()
{
try
{
// Step 1. Get images from blob storage.
BlobHelper BlobHelper = new BlobHelper(StorageAccount, StorageKey);
List <string> blobs = BlobHelper.ListBlobs(Container);
List <string> images = new List <string>();
foreach (var blobName in blobs)
{
images.Add(blobName);
}
// Step 2. For each image, run the face api detection algorithm.
var faceServiceClient = new FaceServiceClient(ServiceKey, "https://westcentralus.api.cognitive.microsoft.com/face/v1.0");
for (int i = 0; i < blobs.Count; i++)
{
using (WebClient client = new WebClient())
{
byte[] fileBytes = client.DownloadData(string.Concat("http://faceapiweu.blob.core.windows.net/cloudprojectsampleimages/", images[i]));
bool exists = System.IO.Directory.Exists(Server.MapPath(directory));
if (!exists)
{
try
{
Directory.CreateDirectory(Server.MapPath(directory));
}
catch (Exception ex)
{
ex.ToString();
}
}
string imageFullPath = Server.MapPath(directory) + '/' + images[i] as string;
System.IO.File.WriteAllBytes(imageFullPath, fileBytes);
using (var stream = client.OpenRead(string.Concat("http://faceapiweu.blob.core.windows.net/cloudprojectsampleimages/", images[i])))
{
//string imageFullPath = "";
//using (Bitmap bmp = new Bitmap(stream))
//{
// imageFullPath = Server.MapPath(directory) + "/original/" + images[i] as string;
// bmp.Save(imageFullPath, ImageFormat.Jpeg);
//}
Face[] faces = await faceServiceClient.DetectAsync(stream, true, true, new FaceAttributeType[] { FaceAttributeType.Gender, FaceAttributeType.Age, FaceAttributeType.Smile, FaceAttributeType.Glasses });
Bitmap CroppedFace = null;
foreach (var face in faces)
{
//Create & Save Cropped Images
var croppedImg = Convert.ToString(Guid.NewGuid()) + ".jpeg" as string;
var croppedImgPath = "../MultiDetectedFiles" + '/' + croppedImg as string;
var croppedImgFullPath = Server.MapPath(directory) + '/' + croppedImg as string;
CroppedFace = CropBitmap(
(Bitmap)Bitmap.FromFile(imageFullPath),
face.FaceRectangle.Left,
face.FaceRectangle.Top,
face.FaceRectangle.Width,
face.FaceRectangle.Height);
CroppedFace.Save(croppedImgFullPath, ImageFormat.Jpeg);
if (CroppedFace != null)
{
((IDisposable)CroppedFace).Dispose();
}
DetectedFaces.Add(new vmFace()
{
ImagePath = null,
FileName = croppedImg,
FilePath = croppedImgPath,
Left = face.FaceRectangle.Left,
Top = face.FaceRectangle.Top,
Width = face.FaceRectangle.Width,
Height = face.FaceRectangle.Height,
FaceId = face.FaceId.ToString(),
Gender = face.FaceAttributes.Gender,
Age = string.Format("{0:#} years old", face.FaceAttributes.Age),
IsSmiling = face.FaceAttributes.Smile > 0.0 ? "Smile" : "Not Smile",
Glasses = face.FaceAttributes.Glasses.ToString(),
});
}
// Convert detection result into UI binding object for rendering.
var imageInfo = UIHelper.GetImageInfoForRenderingFromStream(stream);
var rectFaces = UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo);
foreach (var face in rectFaces)
{
ResultCollection.Add(face);
}
var faceModal = new FaceDetectionModal {
DetectedFaces = DetectedFaces, ResultCollection = ResultCollection
};
this.finalModal.Items.Add(faceModal);
}
}
}
}
catch (Exception ex)
{
Console.Write(ex);
throw;
}
return(View(this.finalModal));
}
